Sentence examples for binary variables using the from inspiring English sources

All these three determinants were initially explored as continuous variables and subsequently categorised as binary variables (using the median value as cut-off) for illustration of the results.

Slow and fast MCI were analyzed as binary variables using the GAM in which the effect of available biomarkers was examined as prognostic factors, separately or in combination (uni- or multivariate GAM analysis).

We programed the statistical software to calculate new optimal cut-off points for continuous variables, generate binary variables using the new cut-off values in each bootstrap sample and run a multiple logistic regression analysis using the backward selection method with all the new binary variables.

In order to find the best-fit model, we transformed the continuous variables into binary variables using the Youden index-J of the receiver operating characteristic (ROC) curve to maximize their discriminative powers of the best-fit model (e.g., age ≥67 years, BMI <22 kg/m).

Consequently, testing for concurrent validity referred to the relationship between the Child-OIDP and the following variables: Perceived satisfaction with mouth (re-categorised into three categories; "low", "moderate" and "high") using the Kruskal-Wallis test, perceived oral health and treatment need (re-categorised into binary variables) using the Mann-Whitney test.

Other continuous variables were converted to binary variables using the following cutoffs: age <65 vs ⩾65 years, RMH score 0 1 vs 2 3, albumin <35 vs ⩾35 g l−1, LDH ⩽upper limit of normal vs >upper limit of normal, absolute neutrophil count ⩽5 × 10 l−1 vs >5 × 10 l−1, and absolute lymphocyte count <0.7 × 10 l−1 vs ⩾0.7 × 10 l−10

Analyses were conducted using dietary iron intake as a continuous variable and a binary variable using the UK RNI cut-off of 14.8 mg/day.

Domain I (uPAR(I)) was treated as a binary variable using the limit of quantification of the assay as the cut-point.

Depressive symptoms were ascertained as a binary variable using the self-completed Edinburgh Postnatal Depression Scale (EPDS), the most widely used screening instrument for perinatal depression in international and Turkish research.

The summed score of the items was categorised into a binary variable using the 88th percentile, as this cut-point has been shown to match the cut-off employed for HADS-Total caseness [ 45].

There was no significant association between Ki-67 and the risk of recurrence both when considering Ki-67 as a continuous variable (HR = 1.01; [95%CI: 0.99-1.03], p = 0.19) or as a binary variable using the cut-off of >15%;(HR = 1.03; [95%CI: 0.51-2.07], p = 0.93).